Linear Algebra, Markov Chains, and Queueing Models (The IMA Volumes in Mathematics and its Applications)

This volume contains articles focusing on the use of linear algebra as an indispensable tool in researching Markov chains and queueing models. Markov chains and queueing models play an increasingly important role in the understanding of complex systems, such as computer, communication, and transportation systems. The articles contained herein bring together practitioners and researchers from the areas of linear algebra, numerical analysis, and queueing theory, who share a common interest of analyzing and solving finite state Markov chains. The articles are grouped into three major categories: perturbation theory and error analysis; iterative methods; and applications regarding queueing models. These papers aim to provide the reader with an enlarged perspective of some of the major issues which are of current concern to both the pure and applied communities.

Carl D. Meyer is Professor of Mathematics at North Carolina State University. His research interests include numerical and applied linear algebra; Markov chains and applied probability; and information retrieval, data mining, and web search. He is the author or co-author of six books.